Results 271 to 280 of about 2,331,313 (323)

AI-discovered tuning laws explain neuronal population code geometry

Tilbury R, Kwon D, Haydaroğlu A, Ratliff J, Schmutz V, Carandini M, Miller K, Stachenfeld K, Harris KD.   +8 more
europepmc   +1 more source

Prompting and Fine-Tuning Large Language Models for Parkinson Disease Diagnosis: Comparative Evaluation Study Using the PPMI Structured Dataset.

JMIR Med Inform
Shin HJ, Jeong YJ, Jun S, Kang DY.
europepmc   +1 more source

Pitch selectivity in ferret auditory cortex

Tarka VM, Gaucher Q, Walker KMM.
europepmc   +1 more source

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Tune-A-Video: One-Shot Tuning of Image Diffusion Models for Text-to-Video Generation

IEEE International Conference on Computer Vision, 2022
To replicate the success of text-to-image (T2I) generation, recent works employ large-scale video datasets to train a text-to-video (T2V) generator. Despite their promising results, such paradigm is computationally expensive.
Jay Zhangjie Wu, Yixiao Ge, Xintao Wang, Weixian Lei, Yuchao Gu, W. Hsu, Ying Shan, Xiaohu Qie, Mike Zheng Shou   +8 more
semanticscholar   +1 more source

Otter: A Multi-Modal Model With In-Context Instruction Tuning

IEEE Transactions on Pattern Analysis and Machine Intelligence, 2023
Recent advances in Large Multimodal Models (LMMs) have unveiled great potential as visual assistants. However, most existing works focus on responding to individual instructions or using previous dialogues for contextual understanding.
Bo Li, Yuanhan Zhang, Liangyu Chen, Jinghao Wang, Jingkang Yang, Ziwei Liu   +5 more
semanticscholar   +1 more source

What Makes Good Data for Alignment? A Comprehensive Study of Automatic Data Selection in Instruction Tuning

International Conference on Learning Representations, 2023
Instruction tuning is a standard technique employed to align large language models to end tasks and user preferences after the initial pretraining phase.
Wei Liu, Weihao Zeng, Keqing He, Yong Jiang, Junxian He   +4 more
semanticscholar   +1 more source

Fine-Tuning Fine-Tuning

2018
Abstract This chapter argues that the fine-tuning argument for the existence of God is a straightforwardly legitimate argument. The fine-tuning argument takes certain features of fundamental physics to confirm the existence of God because these features of fundamental physics are more likely given the existence of God than they are given
Hawthorne, John, Isaacs, Yoaav
openaire   +3 more sources

Instruction Tuning for Large Language Models: A Survey

ACM Computing Surveys, 2023
This paper surveys research works in the quickly advancing field of instruction tuning (IT), a crucial technique to enhance the capabilities and controllability of large language models (LLMs). Instruction tuning refers to the process of further training
Shengyu Zhang, Linfeng Dong, Xiaoya Li, Sen Zhang, Xiaofei Sun, Shuhe Wang, Jiwei Li, Runyi Hu, Tianwei Zhang, Fei Wu, Guoyin Wang   +10 more
semanticscholar   +1 more source